Surgeons use palpation for tasks such as the identification of biological tissues and the localization of blood vessels and boundaries of local inclusions. Human tissues are unavailable for palpation during laparoscopic operations. A device that can help surgeons distinguish different soft tissues is thus desirable. This study proposes an approach for palpation that uses a self-developed video-assisted tactile sensor. The sensing device, which consists of a video camera, a force sensor, and a semispherical head made of polydimethylsiloxane, can measure the contact area and load on an object. A numerical simulation of the indentation process was performed based on the finite element method. The bisection method was used to estimate the Young's modulus of the object by fitting the results of the simulation to the experimental contact area and load. Fresh porcine livers were used to represent soft tissues to verify the approach. Force control was used in the tests and calculations. The average Young's modulus of the fresh porcine livers was 1.1 kPa. To simulate altered tissue, the porcine liver was boiled. The results showed that the modulus of the boiled livers was 25 times higher than that of the fresh porcine livers. Therefore, the proposed approach can distinguish normal tissue from altered tissue, and is thus feasible for palpation.